Buy Low Candidates: Is A Positive Regression Coming For These Two High BABIP Pitchers?

by Connor Henry

The last couple of weeks we’ve taken a good look at some batters with inflated BABIP and some with deflated BABIP. This week, I figured it might be time to look at some pitchers who are suffering from high BABIP. Determining whether pitchers may have regression coming to their BABIP comes down to the Batted Ball data that pitchers tend to have control over. We will specifically look at:

  1. Inducing Soft Contact > League Average 18%
  2. Limiting Hard Contact < League Average 35.6%
  3. Generating Infield Fly Balls (IFFBs) > League Average 10.4%

These next two pitchers we’re going to take a look at are suffering from a BABIP higher than league average (.293). In addition to looking at the aforementioned batted ball data, I’m also going to be referencing comparable pitchers when it comes to batted ball data as to provide a bit of a benchmark to our data.

 

Zack Godley – Arizona Diamondbacks
Coming into 2018 Zack Godley jumped into the Top 120 in National Fantasy Baseball Championship (NFBC) Average Draft Position (ADP). He won over the hearts of fantasy baseball players everywhere when he went from being undrafted in most fantasy leagues to then providing over 150 innings of a 3.37 ERA in 2017. The truth is he completely backed it up with his peripherals. A bit over three months into the 2018 season and Godley is rewarding his once-proud owners with a 5.07 ERA and 1.60 WHIP while sporting a .330 BABIP. Lets break down his batted ball data in comparison to last year shall we?

  1. Soft Contact % (2017/2018): 19 / 22
  2. Hard Contact % (2017/2018): 32 / 38
  3. IFFB % (2017/2018): 8 / 16

As you can probably tell he is inducing plenty of soft contact while also creating automatic outs 16% of the time the ball is put in play with a stellar IFFB%. He is giving up a bit too much hard contact but I for one do not believe this should cause his BABIP to inflate from .280 in 2017 to .330 in 2018. Now, lets take a look at a batted ball comparison with Aaron Nola.

Player
LD%
GB%
FB%
IFFB%
Soft%
Hard%
BABIP
Zack Godley215128162238.330
Aaron Nola195130152127.262

Surprisingly Godley’s batted ball data looks almost identical to Nola’s. The one glaring difference is the hard contact percentage, which is definitely concerning but not nearly enough to warrant an almost 70 point difference in BABIP. By no means am I saying that you should expect Godley to become Nola, but I do believe that he has experienced pretty bad luck when it comes to the balls that people are putting in play.

Verdict: Godley, by all measures, is inducing a lot of the weak contact he was able to last year. His BABIP sits 50 points higher than it did in 2017, which can only be explained by a bit of bad luck. On top of that he is currently dealing with major control issues which seem to be compounding his bad luck to create a nearly unstartable pitcher. While I expect his BABIP to fall back closer to the league average of .293, I cannot confirm that a slight change in fortune will cause him to return back to his 2017 form without sizable improvement in his command.

 

Kevin Gausman – Baltimore Orioles
The 27-year old pitcher has long been one of the most frustrating pitchers to own. On the surface he provides a mid-90s fastball with a solid slider and a downright filthy (when it’s on) splitter. So why does he always seem to leave us wanting more? Let’s look into some of the batted ball data this season in comparison to his last two seasons to see if BABIP has anything to do with his intermittent struggles.

  1. Soft Contact % (2016/2017/2018): 18 / 18 / 18
  2. Hard Contact % (2016/2017/2018): 31 / 32 / 32
  3. IFFB % (2016/2017/2018): 14 / 10 / 12

With remarkably similar batted ball data the last two years, Gausman has run a BABIP of .308 and .336, both a good bit above league average. This year, yet again, he has settled into a .311 BABIP even though he induces league average soft contact, limits hard contact and generates an above average amount of infield fly balls. While this doesn’t prove that regression is on the way, it does confirm that what we may want to consider Gausman a type of trend-setter when it comes to BABIP. Let’s find a similar batted ball profile to compare him to.

Player
LD%
GB%
FB%
IFFB%
Soft%
Hard%
BABIP
Kevin Gausman214633121832.311
Luis Severino214633112232.272

Incredible right?! Severino, a sure-fire ace, has now run a .272 BABIP in back-to-back years with a batted ball profile strikingly similar to Gausman’s. Of course the major difference in this profile is that Severino induces a good amount more soft contact, but every other metric is almost exactly the same. Again, I am not claiming that Gausman should turn into an ace from here on out, I’m simply stating that their batted ball profile supports the idea that they should be able to maintain similar BABIP. This idea however, for multiple years now, has been proven wrong and has further enforced the notion that Gausman really is a “trend-setter” when it comes to BABIP.

Verdict: Gausman is truly one of the most perplexing players to break down. He possesses the sheer “stuff” of a Top 30 pitcher and he has even increased his swinging strike rate to a career high of 11.5%. He is limiting walks to the same rate he did back in 2016 and even producing ground balls at an above average rate. All signs point to him being able to take that next step into the Top 30 starting pitchers, but BABIP seems to constantly hold him back. Three years in a row he has been the victim of an inflated BABIP and unfortunately for him I see no reason for that to change now. Gausman should continue to provide plenty of quality starts with solid strikeout totals but always remember he will be prone to starts where batters will undoubtedly square up his pitches. Unless he is able to become an elite bat-misser or his three-year BABIP trend takes a sudden turn, he seems destined to ride a higher-than-average BABIP to fantasy mediocrity.

Sources: Fangraphs, Brooks Baseball, NFBC

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